Crosstalk Between Female Gonadal Hormones and Vaginal Microbiota Across Various Phases of Women's Gynecological Lifecycle

Abstract

Functional equilibrium between vaginal microbiota and the host is important for maintaining gynecological and reproductive health. Apart from host genetics, infections, changes in diet, life-style and hygiene status are known to affect this delicate state of equilibrium. More importantly, the gonadal hormones strongly influence the overall structure and function of vaginal microbiota. Several studies have attempted to understand (a) the composition of vaginal microbiota in specific stages of women's reproductive cycle as well as in menopause (b) their association with gonadal hormones, and their potential role in manifestation of specific health conditions (from the perspective of cause/consequence). However, a single study that places, in context, the structural variations of the vaginal microbiome across the entire life-span of women's reproductive cycle and during various stages of menopause is currently lacking. With the objective to obtain a holistic overview of the community dynamics of vaginal micro-environment 'across' various stages of women's reproductive and post-reproductive life-cycle, we have performed a meta-analysis of approximately 1,000 vaginal microbiome samples representing various stages of the reproductive cycle and menopausal states. Objectives of this analysis included (a) understanding temporal changes in vaginal community taxonomic structure and composition as women pass through various reproductive and menopausal stages (b) exploring correlations between the levels of female sex hormones with vaginal microbiome diversity (c) analyzing changes in the pattern of community diversity in cases of dysbiotic conditions such as bacterial vaginosis, and viewing the analyzed changes in the context of a healthy state. Results reveal interesting temporal trends with respect to vaginal microbial community diversity and its pattern of correlation with host physiology. Results indicate significant differences in alpha-diversity and overall vaginal microbial community members in various reproductive and post-reproductive phases. In addition to reinforcing the known influence/role of gonadal hormones in maintaining gynecological health, results indicate how hormonal level perturbations cause/contribute to imbalances in vaginal microbiota. The nature of resulting dysbiotic state and its influence on vaginal health is also analyzed and discussed. Results also suggest that elevated vaginal microbial diversity in pregnancy does not necessarily indicate a state of bacterial infection. The study puts forward a hormone-level driven microbiome diversity hypothesis for explaining temporal patterns in vaginal microbial diversity during various stages of women's reproductive cycle and at menopause.

Keywords: alpha-diversity; community dynamics; estrogen; progesterone; reproductive life-cycle; vaginal microbiota.

FIGURE 1

Heatmap representing the taxonomic profiles of vaginal microbial communities at various reproductive and post-reproductive stages of women. Rank-normalized median abundance values (non-zero) of vaginal bacterial groups/taxa across all reproductive stages and post-reproductive of women has been plotted as a heat map. The cells highlighted in blue and red represent low and high abundance of the corresponding bacterial groups. (A) Given that the objective was to observe variations in the abundance pattern of each individual taxon across various reproductive sub-phases, median abundances values of each taxon were rank normalized across various reproductive sub-phases (and not across various taxa in each reproductive sub-phase). Data was therefore subjected to row-wise normalization rather than column-wise. (B) To observe taxonomic variations within each reproductive and post-reproductive stage, column-wise or stage-wise rank normalized median abundance values (non-zero) of vaginal bacterial groups are represented as a heatmap.

FIGURE 2

(A) Principal coordinates analysis (PcoA) plot of datasets based on Weighted Unifrac divergence. The samples analyzed clustered into three distinct clusters/community types based on Weighted Unifrac divergence as a distance metric. Dirichlet Multinomial Mixtures probabilistic model was employed to obtain statistically optimum number of clusters/community types. The corresponding Dirichlet model fit plot representing the number of optimum clusters/community types for the datasets analyzed is provided as Supplementary Figure S2. (B) Percentage distribution of samples in different community types. Distribution of vaginal microbiome samples from discrete reproductive and post-reproductive stages in different community types. The samples from most of the stages are observed to cluster together in community type G1. Majority of the samples from stage BV-Positive and 1st trimester are observed to occur in community type G2. The community type G3 is found to constitute majority of samples from Tanner Stage II and Menstrual stage.

FIGURE 3

(A) Principal coordinate analysis (PcoA) plot of datasets based on Weighted Unifrac divergence, representing three distinct community types. The samples analyzed clustered into three distinct clusters/community types based on Weighted Unifrac divergence as a distance metric. Dirichlet Multinomial Mixtures probabilistic model was employed to obtain statistically optimum number of clusters/community types. The corresponding Dirichlet model fit plot representing the number of optimum clusters/community types for the datasets analyzed is provided as Supplementary Figure S2. (B) Rank normalized weights of genera in different community types. The genera constituting the vaginal microbial communities in the datasets analyzed were ranked based on their weights/probabilities in (a) each community type/cluster and (b) throughout different community types/clusters. This exercise was performed to identify the driving/contributing bacterial taxa/groups for the observed clusters. The community type G1, constituting most of the samples from the stages analyzed is observed to be driven solely by members of Lactobacilli. The genera namely, Gardnerella, Atopobium, Megasphaera, Dialister, Aerococcus, Sneathia, Parvimonas, Gemella, and Ureaplasma are seen to drive/constitute the community type G2. The driving taxa for community type G3 are observed to be Prevotella, Anaerococcus, Peptoniphilus, Finegoldia, Streptococcus, Mobiluncus, and Peptostreptococcus.

FIGURE 4

(A) Shannon, (B) Chao, and (C) Simpson diversity trends across samples corresponding to all reproductive and post-reproductive stages of women.

FIGURE 5

(A) Dynamics of vaginal microbiome in response to female sex hormones. The surge of estrogen and progesterone causes an increased deposition of glycogen on vaginal epithelial walls. Since glycogen serves as a nutrient source for vaginal microbes, the excess amount of glycogen causes a sudden rise in the numbers of glycogen-degrading, lactic-acid producing Lactobacilli. The concomitant release of lactic acid, along with hydrogen peroxide by Lactobacilli inhibits the growth of other microbes. (B) Trends of log-normalized vaginal hormone levels and Shannon–Weiner Diversity Index of vaginal microbiome across all reproductive and post-reproductive stages of women. The values of estrogen and progesterone across all reproductive and post-reproductive stages of women were collated from various literature sources. The Shannon–Weiner Diversity values and the collated hormone values are log-normalized and plotted together. The stages having sudden perturbations in the hormone levels (onset of puberty, i.e., Tanner stage II, menstrual, onset of pregnancy, i.e., 1st trimester) are observed to have a highly diverse vaginal microbiome. On the contrary, other stages are observed to have stable, less diverse vaginal microbiome.

FIGURE 6

Core metabolic functions in various reproductive and menopausal stages. The core metabolic functions (predicted using iVikodak) along with their respective normalized median abundance values (and corresponding ‘bootstrap scores’) across various reproductive and menopausal stages.